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Postdoctoral researcher in marine ecosystems modelling for the Marine and Continental Waters Program
of machine learning and AI algorithms and methods. Knowledge of species distribution models. Catalan and Spanish are valued LanguagesENGLISHLevelGood Research FieldOtherYears of Research Experience1 - 4
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. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group: Atomistic & Molecular Modelling for Catalysis Group Requirements Specific Requirements PhD in Chemistry
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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networks (LessIsMoreModel) The postdoctoral researcher will carry out scientific experiments in the organism Oikopleura dioica with the aim of understanding heart development. The tasks will include genetic
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23 Sep 2025 Job Information Organisation/Company Universitat de Barcelona Department Genetics, Microbiology & Statistics Research Field Biological sciences Researcher Profile Recognised Researcher
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networks (LessIsMoreModel) The postdoctoral researcher will carry out scientific experiments in the organism Oikopleura dioica with the aim of understanding heart development. The tasks will include genetic
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for the processing and analysis of multimodal spatial biology datasets. Design and apply advanced image analysis algorithms for cell segmentation, feature extraction, and debarcoding for lineage tracing. Statistically
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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. Minoru Otani). The post holder will undertake the following tasks: Contribution to the design, implementation, testing and demonstration of new methodologies and algorithms for the study of electrochemical
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, at the molecular and at the organismal levels. Our lab is continuously generating large-scale, state-of-the-art gut metagenomics data for thousands of genetically heterogeneous “HS” laboratory rats whose genetic